Chapter
Scale and Simulation in Robotics and Machine Learning
1:16:04 - 1:21:20 (05:15)
The speaker discusses the potential of adding individual projects and growing scale to achieve large teams of material engineering and ML science to create systems that work at large scale, ultimately leading to the creation of a simulator that can simulate the real world.
Clips
The goal is to create large teams of people in order to run things at a very large scale, with material engineering and machine learning science coming together to create systems that work and get material results that would have otherwise been impossible.
1:16:04 - 1:17:58 (01:54)
Summary
The goal is to create large teams of people in order to run things at a very large scale, with material engineering and machine learning science coming together to create systems that work and get material results that would have otherwise been impossible.
ChapterScale and Simulation in Robotics and Machine Learning
EpisodeGreg Brockman: OpenAI and AGI
PodcastLex Fridman Podcast
The Open AI reasoning team is working towards developing AI that can solve and prove theorems through logic and mathematical reasoning.
1:17:58 - 1:19:18 (01:19)
Summary
The Open AI reasoning team is working towards developing AI that can solve and prove theorems through logic and mathematical reasoning. The ability to do such out of distribution generalization and potentially prove that P equals NP would be a huge achievement.
ChapterScale and Simulation in Robotics and Machine Learning
EpisodeGreg Brockman: OpenAI and AGI
PodcastLex Fridman Podcast
The possibilities of simulated systems and language modeling are much greater than people tend to believe, with language modeling in particular taking a more prominent place in the near future.
1:19:18 - 1:21:20 (02:01)
Summary
The possibilities of simulated systems and language modeling are much greater than people tend to believe, with language modeling in particular taking a more prominent place in the near future.